Heathrow Airports Service Operations Management

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Background

Service quality refers to the perceptions that customers have on the expected quality of services provided. In most airports, service quality is a necessary tool as it enables the assessment of the level of satisfaction that customers have (Johnston 2005, p. 1304). Heathrow airport is the largest and busiest airport in the whole world. In the past few years, the airport had been operating beyond its designed sufficient capacity, which implies that the limit that had been previously set had been raised through the airport had not yet adjusted to fit the new requirements (Project Management Institute 2008). However, the fact that the airport was able to operate beyond its capacity simply means that it was working more efficiently than expected based on its situations. Despite the airports ability to meet the passenger requirements, there were some facilities with bottlenecks that had been stretched to their limit, which had lowered customer service (Chase, Jacobs, & Aquilano 2007).

Consequently, the airport has been continually improving their services to meet the customers expectations and also improve on the service quality gap, that is, the gap that exists between the customers expectations and the level of quality in the airport (BAA 2008). In this paper, the service quality of Heathrow airport is critically evaluated and methods of improving the service quality discussed. The implementation of such services would result in the improvement of services provided by the airport as well as improvements in service quality (HAL 2011).

Objectives of the study

The main objectives of this study are:

  • To critically evaluate service management at Heathrow airport to determine areas that need improvement in service quality
  • To evaluate actions and measures that have been taken to improve the service quality at Heathrow airport

Methodology

The study explores various service operation management aspects of airports in the UK, including Value of Time (VOT), passenger demand forecasts, and capacity management. The study then narrows down to an assessment of Heathrow Airport Limited quality of service, based on the implementation of a Service Quality Rebate (SQR) Scheme, which provides an insight on the inexistent need for the expansion of HAL. The final section of this study involves an analysis of various methods employed by Heathrow airport to improve its quality of service.

Evaluation of UK airports service quality

Value of time (VOT)

The appraisal of various South East and East of England Regional Air Services (SERAS) packages, as well as the evaluation of the broader economic benefits of increasing the capacity of airports in this region, is influenced by multiple factors such as Value of Time (VOT). Studies in the economic impact of business aviation show that the working VOT for business travellers is £62 for each hour during work, while the value for non-working time is £31 (Civil Aviation Authority 2010). These values are dependent on the income of the traveller, which are used to estimate the worth of the air traveller to the economy.

Additionally, the increase in this value is in direct proportion to the rise in GDP per capita, since personal incomes for work flights determine trips. Non-working VOT, on the other hand, is assumed to be half the value of working VOT since it involves flights that are not business or work-related, such as those taken on weekends, and are not compensated. The elevated figures used are based on the assumption that most business travellers are upper-rank management, with massive salary packages. The European Organization for the safety of air navigation for business passengers recommends an average VOT that is lower than that of Heathrow airport (SASIG 2003).

Average VOT recommended by Eurocontrol.
Table 2.1 Average VOT recommended by Eurocontrol.

These values are useful in the analysis of costs and benefits for a period of up to 30 years following the last investment in the expansion of the airport, such as the construction of additional runways, or terminals (DETR 2000).

Passenger Demand forecasts

The passenger forecasts were determined by the DETR in Air Traffic Forecasts for the UK in 2000 (DETR 2000). These values were then entered into an analysis system that assigns air travellers to current and prospect airports based on the current costs, travel-routes surveys, and services provided by each airport. The model used provides for increases in demand over the appraisal period, and the value is maintained when the airport reaches its effective capacity. The system estimates a minimal air traveller increase rate of 3.6% and a maximum rate of 4.9% until 2020 with unconstrained demand growth (DETR 2000). The distribution of passengers among the UK airports is dependent on their overall expenses including road access costs, several flights, flight times and fares for different routes, exchange rates, and economic growth (DETR 2000). The predictions according to the type of travel arrangements are shown in table 2.2:

Table 2.2 passenger predictions by category in millions per annum.

1998 2005 2010 2015 2020 1998-2020% change
UK leisure 50.1 71.6 84.1 98.1 114.1 128%
UK business 10.9 14.6 19.4 25.7 34 212%
foreign leisure 23.6 35.4 44.3 54.9 67.2 185%
foreign business 12.6 18.1 22.9 31.2 40.6 222%
low-cost airlines 6.9 18.7 21.5 24.6 28.2 309%
misc 21.2 28.1 32.8 38.7 45.7 116%
domestic 33.6 42.2 50.2 59.8 71 111%
total 158.9 228.7 275.2 333 400.8 152%

Source: DETR (2000).

The table shows that the number of air passengers in the UK will be at 500 million passengers per annum (mppa) by 2030, with a majority of these travellers using the South East airports. The increase in trips implies that the passengers will spend more time and money in flight. However, the strategic aviation particular interest group (SASIG) claims that these figures are too high and unrealistic (SASIG 2003). The Air Transport Movements (ATM) proposed by DETR are considerably higher than those made by Eurocontrol. The former predicts an ATM growth in the range of 2.6-3.9% and the latter 1.6-1.9% increase in the period beginning from 2003 and ending in 2025. The data does not take into consideration a change in demand to other European airports such as those in Paris or Amsterdam, as well as alternative means of transport besides air travel. However, the effects of these changes are expected to be minimal (Eurocontrol, 2005).

Airfare changes and income elasticity

These two factors are essential in the prediction of passenger demand over time. Income elasticity is taken at a factor of 1.5 to the elasticity for airfare, with no consideration of the possible change in elasticities with time. Income elasticity is exaggerated in the long-term since it is expected to decrease as the market ages, leading to s subsequent decrease in the demand for air travel. Another consideration of the model is a 1% annual drop in airfares based on multiple factors, including variation in oil prices, changes in aircraft technology, competition, and deregulation. The cost reductions may be offset by increments in environmental taxation due to issues of carbon trading (Cook, Bowen, Chase, Dasu, Stewart, & Tansik 2002, p. 166).

Capacity Constraint

The capacity levels of different airports and the constraints posed by exceeding such limits cannot be determined definitively. As such, the estimation of an airports capacity needs can be influenced by airport personnel, resulting in skewed assessments of the current and long-term terminal and runway capacities. Regulated airports show a directly proportional association between the effort made in enhancing infrastructure and proceeds acquired. One of the shortcomings of estimating the capacity of an airport is that it is effortlessly understated. This shortcoming was experienced in HAL when its maximum capacity towards the end of the twentieth century was valued at 50 million passengers. In contrast, it currently operates at a capacity of 68 million passengers per annum. The same problem was observed in the estimation of Stansteds capacity in 2002 at 18 million, though it is currently operating at 21 million passengers (GLA Economics 2006).

The assessment fails to consider various operational alternatives to the capacity dilemma like demand management or enhanced use of accessible capacity. Another shortcoming of the model is its failure to adjust for larger aircraft to manage increasing demand. In a comparison of wake vortex related aircraft separation requirements to extra seating capacity per aircraft, the former would lead to a decrease in the need for additional runway capacity. The increase in aircraft size has led to a lesser increase in passenger ATM compared to the increase in the number of passengers (Davidow 2003, p. 238).

Appendix 1 contains three tables that show the relation between load factor and air travel passengers. The tables show that there would also be an increase in the number of passengers who can travel through the key London airports by over 12 million. Another interesting finding is that raising the mean aircraft size would raise the number of possible air travellers. One shortcoming of such an analysis is that markets do not necessarily support the use of the largest aircraft on all routes, especially when both volume and variety of destinations served raises concerns (Martin, Surridge, & Roman 2011, p. 265). The service quality rebate scheme provides an insight into the assessment of services provided at the Heathrow airport and the impact of congestion on profitability.

The third table in appendix 1, table 2.5, gives an analysis of the additional capacity of all the airports if they attain their maximum ATM, under an assumption of 85% average load factor and larger aircraft size. The analysis of Heathrow airport takes into consideration an enhanced capacity with the implementation of multiple runways, as well as the environmental implications. Based on the figures, there is an estimated total of 80 million additional passengers going through the London airports with no provisions for an extra runway. Based on the assumption that the number of UK air travellers using the London airports is kept constant, then the need for an expansion in the South-East would be postponed to 2013, based on high point demand forecasts, and 2019, based on the low point demand estimates. However, there would be a requirement to accommodate the increasing passenger throughput by enhancing surface access, and other investments (Halcrow 1999, p. 13).

Implementation of the Service Quality Rebate Scheme at Heathrow Airport

Introduction to the SQR scheme

The implementation of the Service Quality Rebate Scheme (SQR) by Heathrow Airport Limited (HAL) is defined by the Civil Aviation Authority (CAA). The SQR was implemented as a means to determine the quality of service provided by the airport, and in turn, influence BAAs revenue from airport charges. The implementation of SQR provided HAL with a financial incentive to meet a set standard of service quality across a range of services, and motivation to increase its performance for the benefit of the passengers. The scheme is characterized by the existence of incentives to the airport to meet set standards of service quality, monthly rebate payments to the airlines, a maximum amount of rebates paid that is set at 7% of airport charges, and payment of rebates based on individual terminal performance (Heathrow 2100). The latter feature implies that different terminals have different performance targets. The Quality of Service monitor (QSM) is used in the determination of passengers perception (Heathrow 2011). The implementation of the scheme is divided into three component activities, as shown in the diagram below.

The components of SQR scheme
Figure 1: the components of SQR scheme.

Data Collection

Queuing measures

The three queuing standards used across the airport include passenger queues for transferring and departing passengers, staff search queues, and vehicle queuing at control posts. The determination of passenger queue times can be conducted manually or automatically. The manual process involves the staff monitoring passengers as they pass through a search area using CCTV, at regular time intervals of around 15 minutes. Deductions are then made to account for start and end times, as well as unimpeded walk times. The automated method used at HAL uses two technologies, namely a laser solution, and Bluetooth detection. The first method uses lasers positioned at the entrance point to check the number of passengers who entered or exited a search area every 5 minutes. The Bluetooth method uses Bluetooth detectors placed at the ceiling of a search area and exit point. The detectors capture the unique Bluetooth signature ID from passengers mobile devices (when set to discoverable), and the averages are obtained in 15-minute intervals.

Representation of the passenger queue times
Figure 2: representation of the passenger queue times.

Staff search queue times are collected by an operator in the Operating Monitoring Centre observing CCTV. The operator manually records the time taken for a member of staff to move from the back of the security queue to the roller bed at the front of the x-ray machines (Elias 2007). Control Post queue times are measured to determine the time taken for a vehicle to move from the back of the vehicle queue to the start of the control post-process without including the time spent by the vehicle within the search area. The periods are captured automatically using a number plate recognition system in 15-minute intervals. Data from the three queues are documented daily and collated before being sent to the finance team for calculation of any rebate due.

QSM measures

The Quality of Service Monitor (QSM) is a BAA customer service monitor implemented in all BAAs UK airports to provide the management with information regarding the performance of the airport. QSM involves face to face interviews with arriving, transfer and departing passengers, to find out information regarding cleanliness, wayfinding, queuing time, and availability of seating. The data is recorded using computer aids such as PDAs. This allows for monthly weighting of data using Statistical Report system based on departure data (country of destination) and arrival data (country of origin). The standards for QSM measures and rebates payable due to failure are indicated in appendix 2.

Asset Availability measures

The methodology employed for data collection of the asset availability measures is dependent on the asset being measured, such as pier service, stand availability, and track transit system. The performance time for various assets is captured using the fault management system. These assets include passenger sensitive equipment such as lifts and escalators, fixed electrical ground power, stand entry guidance system, pre-conditioned air, and arrivals baggage reclaim (HAL 2011).

Aerodrome congestion

Aerodrome congestion is measured on an event by event basis. Rebates are payable when a material event occurs. Material events refer to occurrences that are the responsibility of the airport or its agents, leading to material operational impact in terms of the number of air transport movements lost or deferred. These include staff shortages, critical air traffic control equipment failure, industrial action by staff members, closure of runways, and failure of the taxiway lighting system, among others. The airport maintains a log of these events and calculates the difference between the actual and expected cumulative movements in the determination of rebates (Heathrow 2011).

Rebate Calculation, payment and reporting

The results of all SQR measures are gathered and reviewed for approval by the airports operational management on a monthly basis. This information is then passed on to the finance department for calculation of results and rebates. The calculation of rebates is based on forecast airport charges since non-passenger flights charges are not included. Monthly reports based on the scheme are published in the BAAs website and posters around the terminals. Changes to the rebate scheme can only be effected by agreement between the airport and airlines and approved by the CAA or through revision by the CAA.

Improving the service quality at Heathrow airport

Managing disruptions

Events such as volcanic ash, snowfall, hurricanes, typhoons, bombings have all been found to cause significant disruptions that result in airport closures and flight cancellations. Heathrow airport has been subjected to numerous disruptions, which have lowered their efficiency in the delivery of quality service (Colgate 2001, p. 219). For example, in December 2010, Heathrow airport experienced many flight cancellations due to the fall of snow on the airport (Gremler & Gwinner 2000, p. 85). The impact of such disruptions can be reduced by developing contingency plans (Fitzsimmons & Fitzsimmons, 2004). Such contingency plans must document the need for additional staff and capacity that may be required to handle the increased number of stranded travellers. Also, additional aeroplanes need to be deployed during such incidences (Tanger & Clayton 2009).

Timely arrivals and departure

At Heathrow airport, the predictability and reliability of the schedules are quite complex due to the numerous flights that arrive and depart from the airport. Currently, most of the flights slightly delay due to unavoidable circumstances, and this has a significant impact on service quality. It is imperative that the punctuality in at Heathrow is improved to achieve over 90% flight punctuality. This can be achieved if the flights are within 15 minutes of their scheduled time. To improve punctuality, accurate scheduling is important to ensure flights arrive and depart as expected (Le Boutillier 2005, p. 28).

Personnel training

Personnel training programs should be well-tailored to target each department and impact on all airport employees (Franceschini, Galetto, & Maisano 2007, p.23). The human resource department plays a vital role in identifying training needs for this personnel to ensure tasks are efficiently run and coordinated. This personnel are drawn from a pool of well experienced and trained personnel to provide relevant training (Franceschini, Galetto & Maisano 2007, p. 23). Each employee in the whole organization should be actively involved in making improvements by reducing the response time to customer inquiries and complaints (Hansen & Danaher 1999, p.232).

Capacity management

Changing the rules

The determination of capacity enhancements in UK airports, and specifically in Heathrow airport, was influenced by the analysis performed by SERAS at both the national and European levels. The values used to guide the decision were VOT, demand forecasts, and income and fares elasticity. Another factor that influences Heathrows airport capacity is the impact of operational responses to capacity-related challenges. The rules and regulations that influence various airport attribute impact on the allocation of slots, landing and air traffic control charges. The effect of these rules has been minimal on facilitating effective usage of Heathrow airport capacity, as well as the reduction of congestion. Permitting changes to the current legislation is likely to assist in rectifying the challenge of future demand for air travel and capacity in congested airports such as HAL.

Single Till versus dual till

The single till principle has contributed to reduced landing charges in Heathrow airport compared to smaller airports in the UK. These charges are also influenced by economies of scale and are under the control of CAA. The single till approach implies that airport charges are dependent on both aeronautical and non-aeronautical services provided by the airport. This mode of calculation helps to reduce the landing fees for large airports like HAL since non-aeronautical profits are included in air charges, which makes them more attractive to smaller airports, and also significantly more congested. The approach taken by CAA promotes the use of a double till structure in HAL and other large airlines to raise the landing charges and consequently, reduce congestion and increase service quality provided by the airports (General Aviation n.d).

Role of Single European Sky

One of the components of the single European sky is the functional airspace block (FAB), whose role is to integrate airspace across borders and significantly enhance the use of airport capacity (HAL 2011). The system allows airlines to reserve slots annually as long as they use them 80% of the time, which is a rigid framework that does not adjust effectively with variations in demand conditions of other airports. Changes to this administrative approach would involve the establishment of a system that allocates slots based on airline and passenger demand, causing a bigger supply of flights to be assigned to higher demand airports such as Heathrow. This can be achieved by permitting an exchange of slots between airports. This would imply that value would be set to the slots, allowing the exclusion of numerous marginal flights provided by smaller planes in large airports such as HAL. This would, in turn, free up the capacity of large airports such as Heathrow (General Aviation n.d).

Taxes on air travel

The aviation industry enjoys tax-free services on fuel and tickets, as well as other products provided to air travel passengers, which makes this mode of transportation appealing. An introduction of taxes and duty to some aviation services would reduce passenger demand, hence reducing the need for additional capacity in Heathrow airport and other large airports in the UK (Rowe 2007).

Price regulation

The regulatory framework of UK airports such as HAL by the CAA is aimed at allowing for the efficient and economical operation of airports by setting five-year price caps and discretionary trading conditions. However, price capping does not yield the intended objectives since additional profits are absorbed in the next round of price setting. As such, price capping should be abolished to allow airport operators to set prices based on market trends. Such a strategy would see the prices at Heathrow increase and divert their attention to premium-rate business. This would, in turn, lead to a re-distribution of demand to other airports and decongest the airport with minimal effort (Rowe 2007).

Inclusion of aviation in the EU Emission Trading Scheme

Such a scheme would give aircraft operators the responsibility of complying to the regulations, which would increase airlines costs and fares, leading to less demand for air travel. The trading scheme would lead to a decrease in low volume marginal routes and smaller aircraft flights, and a subsequent focus on high-density routes (HAL 2011).

Conclusion

This study has revealed various challenges faced by airports to remain profitable by ensuring the continued provision of quality service. The study has also shown the factors that influence the value of rebates for BAA airlines, based on the case study of Heathrow airport. Based on the assumption that the demand for air travel will continue to grow, it is necessary for airlines to polish their service operation management to attract a large clientele and increase their profits. The automation of various systems, including passenger check-in systems to reduce congestion, enhanced control systems to increase the number of plane movements and better process management to reduce material events are some of the measures in place to enhance service operation management at Heathrow airport.

Reference List

BAA 2008, Refurbishing Heathrow Airport Terminal 1, On Time, On Budget, With No Disruptions to Travelling Public, Changing the Face at the Busiest Airport in the World through Project Management.

Chase, R B, Jacobs, F, & Aquilano, N.(2007, Operations Management for Competitive Advantage, McGraw-Hill, New York.

Civil Aviation Authority 2010, Audit of Service Quality and Rebate Scheme at Heathrow and Gatwick Airports, Heathrow Airport Findings Report.

Colgate, M 2001, Developing a comprehensive picture of service failure, International Journal of Service Industry Management, vol. 12, no. 3, pp. 215-33.

Cook, L, Bowen, DE, Chase, R B, Dasu, S, Stewart, D M, & Tansik, D A 2002, Human issues in service design, Journal of Operations Management, vol. 20 no. 2, pp. 159-74.

Davidow, M 2003, Organisational responses to customer complaints: what works and what doesnt, Journal of Service Research, vol. 5, no. 3, pp. 225-50.

DETR 2000, Air Traffic Forecasts for the United Kingdom, DETR, London.

Elias, B 2007, Air Cargo Security, CRS Report for Congress.

Eurocontrol 2005, Standard inputs for EUROCONTROL cost benefit analyses, EUROCONTROL, London.

Fitzsimmons, JA, & Fitzsimmons, MJ 2004, Service Management, 4th ed, McGraw-Hill, New York.

Franceschini, F, Galetto, M, & Maisano, D 2007, Management by Measurement, Springer-Verlag, Heidelberg, Berlin.

General Aviation. n.d, Recommended Security action Items for fixed base Operators. Transport Security Administration. Web.

GLA Economics 2006, Heathrow Economics Study: Expansion of Heathrow airport, Colin Buchanan and Partners, London.

Gremler, D.D, & Gwinner, KP 2000, Customer-employee rapport in service relationships, Journal of Service Research, vol. 3, no. 1, pp. 82-104.

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Halcrow 1999, Business Aviation in the South East, The economic Impact of business aviation , no. 2, pp. 12-19.

Hansen, D E & Danaher, PJ 1999, Inconsistent performance during the service encounter, Journal of Service Research, vol. 1 no. 3, pp. 227-35.

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Martin, H, Surridge, M, & Roman, M 2011, Resilient Critical Infrastructure Management With A Service Oriented Architecture: A Test Case Using Airport Collaborative Decision Making, Int. J. Appl. Math. Comput. Sci, Vol. 21, No. 2, 259274.

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Appendices

Appendix 1

Additional capacity arising from enhanced load factors
Table 2.3 Additional capacity arising from enhanced load factors
Additional capacity due to 85% load factors and larger aircraft size
Table 2.4 Additional capacity due to 85% load factors and larger aircraft size.
Additional capacity with maximum ATM, 85% load factor and larger aircraft sizes
Table 2.6 Additional capacity with maximum ATM, 85% load factor and larger aircraft sizes.

Appendix 2

Standards for QSM measures and rebates payable due to failure
Table 3.1: standards for QSM measures and rebates payable due to failure.

Appendix 3

Standards for asset availability measures and rebates payable in the event of failure
Table 3.2: standards for asset availability measures and rebates payable in the event of failure.

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